scholarly journals Human Protein Reference Database

2004 ◽  
Vol 5 (1) ◽  
pp. 4-4 ◽  
Author(s):  
Natalie Wilson
Keyword(s):  
Human Protein Reference Database ◽  
Human Protein ◽  
Reference Database

scholarly journals Human protein reference database--2006 update

2006 ◽  
Vol 34 (90001) ◽  
pp. D411-D414 ◽  
Author(s):  
G. R. Mishra
Keyword(s):  
Human Protein Reference Database ◽  
Human Protein ◽  
Reference Database

Human Protein Reference Database

2004 ◽  
Vol 5 (1) ◽  
pp. 8-8 ◽  
Author(s):  
Natalie Wilson
Keyword(s):  
Human Protein Reference Database ◽  
Human Protein ◽  
Reference Database

scholarly journals Human Protein Reference Database and Human Proteinpedia as resources for phosphoproteome analysis

2012 ◽  
Vol 8 (2) ◽  
pp. 453-463 ◽  
Author(s):  
Renu Goel ◽  
H. C. Harsha ◽  
Akhilesh Pandey ◽  
T. S. Keshava Prasad
Keyword(s):  
Human Protein Reference Database ◽  
Human Protein ◽  
Reference Database

scholarly journals Human Protein Reference Database--2009 update

2009 ◽  
Vol 37 (Database) ◽  
pp. D767-D772 ◽  
Author(s):  
T. S. Keshava Prasad ◽  
R. Goel ◽  
K. Kandasamy ◽  
S. Keerthikumar ◽  
S. Kumar ◽  
...  
Keyword(s):  
Human Protein Reference Database ◽  
Human Protein ◽  
Reference Database

Human Protein Reference Database and Human Proteinpedia as Discovery Resources for Molecular Biotechnology

2010 ◽  
Vol 48 (1) ◽  
pp. 87-95 ◽  
Author(s):  
Renu Goel ◽  
Babylakshmi Muthusamy ◽  
Akhilesh Pandey ◽  
T. S. Keshava Prasad
Keyword(s):  
Human Protein Reference Database ◽  
Human Protein ◽  
Reference Database ◽  
Molecular Biotechnology

scholarly journals Human protein reference database as a discovery resource for proteomics

2004 ◽  
Vol 32 (90001) ◽  
pp. 497D-501 ◽  
Author(s):  
S. Peri
Keyword(s):  
Human Protein Reference Database ◽  
Human Protein ◽  
Reference Database

scholarly journals Prediction of human protein–protein interaction by a mixed Bayesian model and its application to exploring underlying cancer-related pathway crosstalk

2010 ◽  
Vol 8 (57) ◽  
pp. 555-567 ◽  
Author(s):  
Yan Xu ◽  
Wen Hu ◽  
Zhiqiang Chang ◽  
Huizi DuanMu ◽  
Shanzhen Zhang ◽  
...  
Keyword(s):  
Protein Interaction ◽  
Bayesian Model ◽  
Mixed Model ◽  
Prediction Method ◽  
Human Protein Reference Database ◽  
Human Protein ◽  
Reference Database ◽  
Protein Protein Interaction ◽  
Interaction Database ◽  
Pathway Crosstalk

Protein–protein interaction (PPI) prediction method has provided an opportunity for elucidating potential biological processes and disease mechanisms. We integrated eight features involving proteomic, genomic, phenotype and functional annotation datasets by a mixed model consisting of full connected Bayesian (FCB) model and naive Bayesian model to predict human PPIs, resulting in 40 447 PPIs which contain 2740 common PPIs with the human protein reference database (HPRD) by a likelihood ratio cutoff of 512. Then we applied them to exploring underlying pathway crosstalk where pathways were derived from the pathway interaction database. Two pathway crosstalk networks (PCNs) were constructed based on PPI sets. The PPI sets were derived from two different sources. One source was strictly the HPRD database while the other source was a combination of HPRD and PPIs predicted by our mixed Bayesian method. We demonstrated that PCNs based on the mixed PPI set showed much more underlying pathway interactions than the HPRD PPI set. Furthermore, we mapped cancer-causing mutated somatic genes to PPIs between significant pathway crosstalk pairs. We extracted highly connected clusters from over-represented subnetworks of PCNs, which were enriched for mutated gene interactions that acted as crosstalk links. Most of the pathways in top ranking clusters were shown to play important roles in cancer. The clusters themselves showed coherent function categories pertaining to cancer development.

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